Advanced load balancing techniques using MIMO fuzzy logic: A panel distribution case study at state polytechnic of Malang
The issue of unbalance in electrical distribution systems is a significant challenge that requires effective management to ensure stability, reliability, and safety. Load imbalance can result in overheating of transformers and other electrical equipment, reducing their operational life and increasin...
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Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2025-06-01
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Series: | MethodsX |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2215016125000457 |
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Summary: | The issue of unbalance in electrical distribution systems is a significant challenge that requires effective management to ensure stability, reliability, and safety. Load imbalance can result in overheating of transformers and other electrical equipment, reducing their operational life and increasing the risk of failure, even leading to power outages.A study employed fuzzy logic to address the problem, achieving load balancing through the utilization of the Sugeno Fuzzy Logic method. The objective of this research is to make a significant contribution to improving the efficiency, reliability, and scalability of the power distribution system, with the ultimate goal of maximizing the use of electrical equipment.It will facilitate the implementation of more intelligent and adaptive decision-making processes. The method is as follows: • The fuzzy approach used a multi-input multi-output (MIMO) system with rule-base 3 × 3 × 3 matrix. • The Sugeno method was selected due to its utilization of a constant mathematical function. This approach offers the benefit of straightforward computation, which can enhance the system's speed and efficiency. • The results showed that the initial load imbalance was 30.86 %, reduced to 5.59 % after the application of load balancing, this is following the IEEE std 446–1995 which allows the maximum load imbalance percentage to be 5–20 %. |
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ISSN: | 2215-0161 |